Informatics Competency and Technology Self-Efficacy Levels Among Undergraduate Nursing Students: Cross-Sectional...

The Saudi Arabian health care sector is transforming under Vision 2030 with the goal of digitizing its services. This necessitates a digitally prepared nursing workforce; however, there is evidence suggesting that nursing students have limited informatics competency and that these skills are minimally covered in their training programs.

This study measured the baseline informatics competency and technology self-efficacy of undergraduate nursing students at the University of Hail, Saudi Arabia.

Using a descriptive cross-sectional design, data were collected from 243 undergraduate nursing students at the University of Hail through an online survey. The survey measured demographics, informatics competency (Canadian Nurse Informatics Competency Assessment Scale), and digital technology self-efficacy. Data analysis used descriptive statistics, 2-tailed t tests, ANOVA, and hierarchical regression analysis.

Students reported a moderate level of informatics competency, with a mean Canadian Nurse Informatics Competency Assessment Scale item score of 2.57 (SD 0.84) on a scale from 1 to 4. They also showed moderate to high self-efficacy for digital technology, with a mean item score of 2.7 (SD 0.56) out of 4. Informatics competency scores were substantially higher in students with prior informatics training and frequent electronic health record exposure. In the underpowered exploratory hierarchical regression model, self-efficacy for digital technology showed a small positive association with informatics competency that approached statistical significance; however, the overall model was not statistically significant and explained only a limited proportion of the variance.

This single-site study of undergraduate nursing students at the University of Hail found moderate self-reported informatics competency despite higher digital technology self-efficacy, indicating a need for strengthened informatics education to support the Saudi Vision 2030. While underpowered, exploratory analyses and self-report data mean that these institution-specific findings should be interpreted cautiously and used primarily to guide future multisite and mixed methods research.